Physicochemical Profiling, Bioactive Properties, and Spectroscopic Fingerprinting of Cow’s Milk from the Pampas Valley (Tayacaja, Peru): A Chemometric Approach to Geographical Differentiation

This study aimed to characterize the physicochemical and functional properties of bovine milk from four districts (Acraquia, Ahuaycha, Pampas, and Daniel Hernández) of the Pampas Valley, Tayacaja province, Huancavelica (Peru), and assess its geographical traceability using vibrational spectroscopy and chemometric tools. Milk samples were analyzed for composition (fat, protein, lactose, salts), fatty acid profile, total phenolic compounds (TPC), antioxidant capacity (AC), and spectral features using mid-infrared (MIR) and Raman spectroscopy. The results revealed significant compositional differences among localities, particularly in fat, protein, and salt content, with Daniel Hernández milk showing higher nutritional density. The fatty acid profile, although statistically similar across districts, highlighted a favorable nutritional composition dominated by oleic, palmitic, and stearic acids. TPC and AC values were homogeneous among districts, reflecting similar feeding and management practices. Molecular vibration analysis via MIR and Raman spectroscopy allowed for the identification of key biochemical differences, particularly in lipid and carbohydrate regions. SIMCA classification models, based on MIR spectral data, successfully discriminated samples by origin with Inter-Class Distance (ICD) values exceeding 3, confirming statistically significant separation. Discriminating power plots revealed that proteins (amide I), lactose (C-O, C-C), and lipid-associated bands (C=O, CH<sub>2</sub>) were major contributors to class differentiation. These findings demonstrate the effectiveness of combining spectroscopic and chemometric approaches to trace the geographical origin of milk and provide scientific support for potential quality labeling systems. This methodology contributes to ensuring product authenticity, promoting regional value-added dairy production, and supporting sustainable rural development in high-Andean ecosystems.

Authors

Institutions

Publication Details

Journal
Molecules
Published
2025-11-20
DOI
https://doi.org/10.3390/molecules30224484
Primary Topic
Milk Quality and Mastitis in Dairy Cows
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Physicochemical Profiling, Bioactive Properties, and Spectroscopic Fingerprinting of Cow’s Milk from the Pampas Valley (Tayacaja, Peru): A Chemometric Approach to Geographical Differentiation

Harold Pawel Johao Oré Quiroz, Gino Paúl Prieto Rosales, Eudes Villanueva, Gustavo Puma-Isuiza et al.
Molecules
Milk Quality and Mastitis in Dairy Cows
article

Physicochemical Profiling, Bioactive Properties, and Spectroscopic Fingerprinting of Cow’s Milk from the Pampas Valley (Tayacaja, Peru): A Chemometric Approach to Geographical Differentiation

Harold Pawel Johao Oré Quiroz, Gino Paúl Prieto Rosales, Eudes Villanueva, Gustavo Puma-Isuiza, Elza Aguirre, Beetthssy Zzussy Hurtado-Soria, Raquel N. Veliz-Sagarvinaga, Yaser M. Chavez-Solano
article en

Abstract

This study aimed to characterize the physicochemical and functional properties of bovine milk from four districts (Acraquia, Ahuaycha, Pampas, and Daniel Hernández) of the Pampas Valley, Tayacaja province, Huancavelica (Peru), and assess its geographical traceability using vibrational spectroscopy and chemometric tools. Milk samples were analyzed for composition (fat, protein, lactose, salts), fatty acid profile, total phenolic compounds (TPC), antioxidant capacity (AC), and spectral features using mid-infrared (MIR) and Raman spectroscopy. The results revealed significant compositional differences among localities, particularly in fat, protein, and salt content, with Daniel Hernández milk showing higher nutritional density. The fatty acid profile, although statistically similar across districts, highlighted a favorable nutritional composition dominated by oleic, palmitic, and stearic acids. TPC and AC values were homogeneous among districts, reflecting similar feeding and management practices. Molecular vibration analysis via MIR and Raman spectroscopy allowed for the identification of key biochemical differences, particularly in lipid and carbohydrate regions. SIMCA classification models, based on MIR spectral data, successfully discriminated samples by origin with Inter-Class Distance (ICD) values exceeding 3, confirming statistically significant separation. Discriminating power plots revealed that proteins (amide I), lactose (C-O, C-C), and lipid-associated bands (C=O, CH<sub>2</sub>) were major contributors to class differentiation. These findings demonstrate the effectiveness of combining spectroscopic and chemometric approaches to trace the geographical origin of milk and provide scientific support for potential quality labeling systems. This methodology contributes to ensuring product authenticity, promoting regional value-added dairy production, and supporting sustainable rural development in high-Andean ecosystems.

MoleculesVol. 30(22)
National Autonomous University of Nicaragua (NI), Universidad Nacional del Santa (PE), Universidad Nacional Agraria La Molina (PE)
Openalex Percentile: Top 54%
Milk Quality and Mastitis in Dairy Cows
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.